Clarify pydata#8728 in docs

- Add reference to numpy docs on view / copies in the corresponding section of the xarray docs, to help clarify pydata#8728 .
- Add note that `da.values()` returns a view in the header for `da.values()`.

doc/user-guide/indexing.rst

@@ -747,7 +747,7 @@ Whether array indexing returns a view or a copy of the underlying
 data depends on the nature of the labels.
 
 For positional (integer)
-indexing, xarray follows the same rules as NumPy:
+indexing, xarray follows the same `rules`_ as NumPy:
 
 * Positional indexing with only integers and slices returns a view.
 * Positional indexing with arrays or lists returns a copy.
@@ -764,8 +764,10 @@ Whether data is a copy or a view is more predictable in xarray than in pandas, s
 unlike pandas, xarray does not produce `SettingWithCopy warnings`_. However, you
 should still avoid assignment with chained indexing.
 
-.. _SettingWithCopy warnings: https://pandas.pydata.org/pandas-docs/stable/indexing.html#returning-a-view-versus-a-copy
+Note that other operations (such as :py:meth:`~xarray.DataArray.values`) may also return views rather than copies.
 
+.. _SettingWithCopy warnings: https://pandas.pydata.org/pandas-docs/stable/indexing.html#returning-a-view-versus-a-copy
+.. _rules: https://numpy.org/doc/stable/user/basics.copies.html
 
 .. _multi-level indexing:
 

xarray/core/dataarray.py

@@ -761,7 +761,7 @@ def data(self, value: Any) -> None:
     @property
     def values(self) -> np.ndarray:
         """
-        The array's data as a numpy.ndarray.
+        A view onto the DataArray's underlying data as a numpy.ndarray.
 
         If the array's data is not a numpy.ndarray this will attempt to convert
         it naively using np.array(), which will raise an error if the array